CHARMM-GUI Multicomponent Assembler for modeling and simulation of complex multicomponent systems

Atomic-scale molecular modeling and simulation are powerful tools for computational biology. However, constructing models with large, densely packed molecules, non-water solvents, or with combinations of multiple biomembranes, polymers, and nanomaterials remains challenging and requires significant time and expertise. Furthermore, existing tools do not support such assemblies under the periodic boundary conditions (PBC) necessary for molecular simulation. Here, we describe Multicomponent Assembler in CHARMM-GUI that automates complex molecular assembly and simulation input preparation under the PBC. In this work, we demonstrate its versatility by preparing 6 challenging systems with varying density of large components: (1) solvated proteins, (2) solvated proteins with a pre-equilibrated membrane, (3) solvated proteins with a sheet-like nanomaterial, (4) solvated proteins with a sheet-like polymer, (5) a mixed membrane-nanomaterial system, and (6) a sheet-like polymer with gaseous solvent. Multicomponent Assembler is expected to be a unique cyberinfrastructure to study complex interactions between small molecules, biomacromolecules, polymers, and nanomaterials.

We found that D(z) varies substantially by Z position, even within the polymer center, as CO2 molecules find defects in the polymer structure where local diffusion is increased on short time scales.The mean of diffusion across bins in the polymer center was calculated to be almost 2x larger for PET95 (7.8 ± 2.2 cm 2 /s × 10 -8 ) than PEF95 (4.0 ± 0.3 cm 2 /s × 10 -8 ), possibly due to there being more defects within the PET95 structure.Of the studies of CO2 diffusion in PET we surveyed (Table S1), the most similar rate is in a simulation (2.43 cm 2 /s × 10 -7 at 25 °C) which used lag times on the order of picoseconds.An experimental study 2 reported much slower CO2 diffusion (7.2 ± 2 cm 2 /s × 10 -11 and 2.2 ± 0.4 cm 2 /s × 10 -9 for PEF and PET, respectively), however their finding that CO2 diffuses more slowly through PEF than PET is consistent with ours.That study measured permeation more directly via changes in atmospheric pressure across a macroscopic plastic barrier, whereas our study measures diffusion by tracking individual particles in a microscopic barrier.
To compare with other diffusion studies, it should be noted that the scale of D(z) depends on τ; the smaller timescales of simulations necessitate smaller τ values, which tends to overestimate longterm diffusion compared to experiments.The utility of simulation studies in this domain is thus by comparison of relative diffusion rates, rather than calculation of absolute diffusion rates.

Mica + POPC Preparation
In Nanomaterial Modeler (https://charmm-gui.org/input/nanomaterial), we selected Mica > Muscovite from the Nanomaterial Type menu.In Box Options, we entered the approximate lengths of X = 100, Y = 100, and Z = 30.Nanomaterial Modeler automatically rounds up to the nearest unit cell size for the selected material (displayed in parentheses), which in this case is X = 103.8Å, Y = 108.2Å, and Z = 30.1 Å.
After clicking "Next", it took about 2 minutes to build this mica model.On the next page, we ignored all options and selected "download .tgz" to obtain the mica-only model.We extracted the .tgzarchive, located the files named step1_nanomaterial.psfand step1_nanomaterial.crd,and renamed them to muscovite.psfand muscovite.crd,respectively.We also used the values for A, B, and C in step1_nanomaterial.stras the reference values for Multicomponent Assembler.
In Multicomponent Assembler, we uploaded the muscovite PSF/CRD files, and clicked "Next".On the size determination page (STEP 1), we set the component type of muscovite to "Periodic".In the Periodic Component Size table, we used the values A and B saved in step1_nanomaterial.strfor the length of X and Y, respectively (i.e., X = 103.836,Y = 108.1836)and estimated Z as ZMAX -ZMIN from the same file (i.e., Z = 29.92).We estimated the thickness of a pure POPC membrane as 46.86 and set the water thickness to 23.43.In the Periodic Components table, we clicked "Set Position" to leave space for a 10 Å thick layer of water between the bottom leaflet of POPC and muscovite by using the default constraint type and positioning type ("Fixed Z position" and "Center of mass", respectively) and set the component position to 48.33.After clicking "Calculate System Size" and "Next", we set the ratio of POPC to 1 in both leaflets, clicked "Show the system info", and clicked "Next".On the next page, we set the ion placing method to "Monte-Carlo" and used 0.15 M KCl and clicked "Next".On the Solvent Options page, we used default values, clicked "Calculate Solvent Composition", then clicked "Next".On the Input Options page, we selected "OpenMM" input generation, "NPT ensemble", and a temperature of 298.15 K.After input generation completed, we downloaded the result with "download .tgz".
We followed the procedure in the previous paragraph to create the Mica + POPC models with a 20 Å and 30 Å water gap, except that the component position of muscovite was set to 58.33 and 68.33, respectively.Since we did not use the default equilibration scheme, we made the following changes to each model's OpenMM input options.In step6.3_equilibration.inpthrough step6.6_equilibration.inp,we changed "pcouple" from "no" to "yes" and added the following lines: Additionally, for step6.6_equilibration.inp,we increased the number of steps (nstep) from "250000" to "1250000".Algorithm 1. Packing optimization.A greedy search of translation and rotation space for a given component (comp).cmax is the maximum allowed number of collisions.dcut is the distance around any atom in comp to check for collisions.δθ is the rotation increment.θ0 is the initial rotation angle along each axis.θmax is the maximum rotation angle along each axis.Collision

Table 2 .
detection ignores CG particles if any have not yet been replaced.Analysis of various programs for multicomponent molecular assemblies."Special script" refers to a scripting language created specifically for a given modeling program.Topology preparation is "automatic" if individual molecule topologies can be inferred or read from a database and "manual" if they must be provided separately by the user.

Table 3 .
Molecules used in benchmark.10 copies (easy) and 8 copies (hard) of each molecule were packed into cubic geometries.

Table 4 .
System configurations used in this study.